OPTIMUM RATIO OF CALCIUM AND BORON IN THE NUTRIENT SOLUTION OR IN CASTOR BEAN SHOOT FOR FRUIT YIELD AND SEED OIL CONTENT

Calcium (Ca) and boron (B) have been reported as the major macro-and micronutrient required for castor bean plant yield. The objective of this study was to determine the Ca: B ratios (in the growth media and plant tissue) for fruit yield and shoot dry weight of the castor bean (Ricinus communis L.), grown in a nutrient solution, and to evaluate Ca and B supply on concentration and total uptake of Ca, potassium (K), magnesium (Mg), and B, as well on the seed oil content. The treatments were arranged in a 3 x 3 factorial fashion, consisting of three rates of Ca (40, 80, and 160 mg L-1) and three of B (0.32, 0.96, and 1.60 mg L-1). Calcium and B rates increased the shoot and root dry weight and fruit yield at a Ca: B ratio in the nutrient solution of 166 and 100, respectively. Symptoms of B deficiency were observed in plants supplied with 0.32 mg B L-1, regardless of the Ca concentration in the nutrient solution. Plants which showed visual symptoms of Ca deficiency cultivated with 40 mg Ca L-1 presented concentration of Ca in plant tissue up to 10 g kg(-1). The concentration and total Ca and B uptake increased with the rates of them. Notwithstanding, the shoot Ca accumulation was improved by B rates. In addition, there were no decreases in K and Mg uptake due to Ca rates. Furthermore, addition of 80 mg L-1 of Ca and 1.60 mg L-1 of B in the growth media increased the seed oil content. The Ca: B ratio in the diagnostic leaf associated with the highest plant dry weight (shoot and root) and fruit yield, was 500 (16 to 20 g kg(-1) of Ca, and for 30 to 40 mg kg(-1) of B).

Semi-supervised dimensionality reduction based on partial least squares for visual analysis of high dimensional data

Dimensionality reduction is employed for visual data analysis as a way to obtaining reduced spaces for high dimensional data or to mapping data directly into 2D or 3D spaces. Although techniques have evolved to improve data segregation on reduced or visual spaces, they have limited capabilities for adjusting the results according to user's knowledge. In this paper, we propose a novel approach to handling both dimensionality reduction and visualization of high dimensional data, taking into account user's input. It employs Partial Least Squares (PLS), a statistical tool to perform retrieval of latent spaces focusing on the discriminability of the data. The method employs a training set for building a highly precise model that can then be applied to a much larger data set very effectively. The reduced data set can be exhibited using various existing visualization techniques. The training data is important to code user's knowledge into the loop. However, this work also devises a strategy for calculating PLS reduced spaces when no training data is available. The approach produces increasingly precise visual mappings as the user feeds back his or her knowledge and is capable of working with small and unbalanced training sets.

Visual impairment in children with spastic cerebral palsy measured by psychophysical and electrophysiological grating acuity tests

Background: This study measured grating visual acuity in 173 children between 6-48 months of age who had different types of spastic cerebral palsy (CP). Method: Behavioural acuity was measured with the Teller Acuity Cards (TAC) using a staircase psychophysical procedure. Electrophysiological visual acuity was estimated using the sweep VEP (sVEP). Results: The percentage of children outside the superior tolerance limits was 44 of 63 (69%) and 50 of 55 (91%) of tetraplegic, 36 of 56 (64%) and 42 of 53 (79%) of diplegic, 10 of 48 (21%) and 12 of 40 (30%) of hemiplegic for sVEP and TAC, respectively. For the sVEP, the greater visual acuity deficit found in the tetraplegic group was significantly different from that of the hemiplegic group (p < 0.001). In the TAC procedure the mean visual acuity deficits of the tetraplegic and diplegic groups were significantly different from that of hemiplegic group (p < 0.001). The differences between sVEP and TAC means of visual acuity difference were statistically significant for the tetraplegic (p < 0.001), diplegic (p < 0.001), and hemiplegic group (p = 0.004). Discussion: Better visual acuities were obtained in both procedures for hemiplegic children compared to diplegic or tetraplegic. Tetraplegic and diplegic children showed greater discrepancies between the TAC and sVEP results. Inter-ocular acuity difference was more frequent in sVEP measurements. Conclusions: Electrophysiologically measured visual acuity is better than behavioural visual acuity in children with CP.

Decreasing the number of false positives in sequence classification

Abstract Background A large number of probabilistic models used in sequence analysis assign non-zero probability values to most input sequences. To decide when a given probability is sufficient the most common way is bayesian binary classification, where the probability of the model characterizing the sequence family of interest is compared to that of an alternative probability model. We can use as alternative model a null model. This is the scoring technique used by sequence analysis tools such as HMMER, SAM and INFERNAL. The most prevalent null models are position-independent residue distributions that include: the uniform distribution, genomic distribution, family-specific distribution and the target sequence distribution. This paper presents a study to evaluate the impact of the choice of a null model in the final result of classifications. In particular, we are interested in minimizing the number of false predictions in a classification. This is a crucial issue to reduce costs of biological validation. Results For all the tests, the target null model presented the lowest number of false positives, when using random sequences as a test. The study was performed in DNA sequences using GC content as the measure of content bias, but the results should be valid also for protein sequences. To broaden the application of the results, the study was performed using randomly generated sequences. Previous studies were performed on aminoacid sequences, using only one probabilistic model (HMM) and on a specific benchmark, and lack more general conclusions about the performance of null models. Finally, a benchmark test with P. falciparum confirmed these results. Conclusions Of the evaluated models the best suited for classification are the uniform model and the target model. However, the use of the uniform model presents a GC bias that can cause more false positives for candidate sequences with extreme compositional bias, a characteristic not described in previous studies. In these cases the target model is more dependable for biological validation due to its higher specificity.

The nature of extremely red galaxies in the local universe

We investigate the nature of extremely red galaxies (ERGs), objects whose colours are redder than those found in the red sequence present in colour–magnitude diagrams of galaxies. We selected from the Sloan Digital Sky Survey Data Release 7 a volume-limited sample of such galaxies in the redshift interval 0.010 < z < 0.030, brighter than Mr = −17.8 (magnitudes dereddened, corrected for the Milky Way extinction) and with (g − r) colours larger than those of galaxies in the red sequence. This sample contains 416 ERGs, which were classified visually. Our classification was cross-checked with other classifications available in the literature. We found from our visual classification that the majority of objects in our sample are edge-on spirals (73 per cent). Other spirals correspond to 13 per cent, whereas elliptical galaxies comprise only 11 per cent of the objects. After comparing the morphological mix and the distributions of Hα/Hβ and axial ratios of ERGs and objects in the red sequence, we suggest that dust, more than stellar population effects, is the driver of the red colours found in these extremely red galaxies.

Verbal and visual stimulation effects on rectus femoris and biceps femoris muscles during isometric and concentric

Abstract Background: Coactivation may be both desirable (injury prevention) or undesirable (strength measurement). In this context, different styles of muscle strength stimulus have being investigated. In this study we evaluated the effects of verbal and visual stimulation on rectus femoris and biceps femoris muscles contraction during isometric and concentric. Methods: We investigated 13 men (age =23.1 ± 3.8 years old; body mass =75.6 ± 9.1 kg; height =1.8 ± 0.07 m). We used the isokinetic dynamometer BIODEX device and an electromyographic (EMG) system. We evaluated the maximum isometric and isokinetic knee extension and flexion at 60°/s. The following conditions were evaluated: without visual nor verbal command (control); verbal command; visual command and; verbal and visual command. In relation to the concentric contraction, the volunteers performed five reciprocal and continuous contractions at 60°/s. With respect to isometric contractions it was made three contractions of five seconds for flexion and extension in a period of one minute. Results: We found that the peak torque during isometric flexion was higher in the subjects in the VVC condition (p > 0.05). In relation to muscle coactivation, the subjects presented higher values at the control condition (p > 0.05). Conclusion We suggest that this type of stimulus is effective for the lower limbs.

A system for classification of time-series data from industrial non-destructive device

This work proposes a system for classification of industrial steel pieces by means of magnetic nondestructive device. The proposed classification system presents two main stages, online system stage and off-line system stage. In online stage, the system classifies inputs and saves misclassification information in order to perform posterior analyses. In the off-line optimization stage, the topology of a Probabilistic Neural Network is optimized by a Feature Selection algorithm combined with the Probabilistic Neural Network to increase the classification rate. The proposed Feature Selection algorithm searches for the signal spectrogram by combining three basic elements: a Sequential Forward Selection algorithm, a Feature Cluster Grow algorithm with classification rate gradient analysis and a Sequential Backward Selection. Also, a trash-data recycling algorithm is proposed to obtain the optimal feedback samples selected from the misclassified ones.

Supervised classification of basaltic aggregate particles based on texture properties

The strength and durability of materials produced from aggregates (e.g., concrete bricks, concrete, and ballast) are critically affected by the weathering of the particles, which is closely related to their mineral composition. It is possible to infer the degree of weathering from visual features derived from the surface of the aggregates. By using sound pattern recognition methods, this study shows that the characterization of the visual texture of particles, performed by using texture-related features of gray scale images, allows the effective differentiation between weathered and nonweathered aggregates. The selection of the most discriminative features is also performed by taking into account a feature ranking method. The evaluation of the methodology in the presence of noise suggests that it can be used in stone quarries for automatic detection of weathered materials.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Classificazione di oggetti in immagini attraverso il modello Bag of Visual Words

Generic object recognition is an important function of the human visual system and everybody finds it highly useful in their everyday life. For an artificial vision system it is a really hard, complex and challenging task because instances of the same object category can generate very different images, depending of different variables such as illumination conditions, the pose of an object, the viewpoint of the camera, partial occlusions, and unrelated background clutter. The purpose of this thesis is to develop a system that is able to classify objects in 2D images based on the context, and identify to which category the object belongs to. Given an image, the system can classify it and decide the correct categorie of the object. Furthermore the objective of this thesis is also to test the performance and the precision of different supervised Machine Learning algorithms in this specific task of object image categorization. Through different experiments the implemented application reveals good categorization performances despite the difficulty of the problem. However this project is open to future improvement; it is possible to implement new algorithms that has not been invented yet or using other techniques to extract features to make the system more reliable. This application can be installed inside an embedded system and after trained (performed outside the system), so it can become able to classify objects in a real-time. The information given from a 3D stereocamera, developed inside the department of Computer Engineering of the University of Bologna, can be used to improve the accuracy of the classification task. The idea is to segment a single object in a scene using the depth given from a stereocamera and in this way make the classification more accurate.

Etablierung eines high content imaging-basierten in vitro Testsystems zur Evaluierung genotoxischer Substanzen

Zur Registrierung von Pharmazeutika ist eine umfassende Analyse ihres genotoxischen Potentials von Nöten. Aufgrund der Vielzahl genotoxischer Mechanismen und deren resultierenden Schäden wird ein gestaffeltes Testdesign durch die ICH-Richtlinie S2(R1) „Guidance on genotoxicity testing and data interpretation for pharmaceuticals intended for human use S2(R1)“ definiert, um alle genotoxischen Substanzen zu identifizieren. Die Standardtestbatterie ist in der frühen Phase der Arzneimittelentwicklung aufgrund des geringen Durchsatzes und des Mangels an verfügbarer Substanzmenge vermindert anwendbar. Darüber hinaus verfügen in vitro Genotoxizitätstests in Säugerzellen über eine relativ geringe Spezifität. Für eine vollständige Sicherheitsbeurteilung wird eine in vivo Testung auf Kanzerogenität benötigt. Allerdings sind diese Testsysteme kosten- und zeitintensiv. Aufgrund dessen zielen neue Forschungsansätze auf die Verbesserung der Prädiktivität und die Erfassung des genotoxischen Potentials bereits in der frühen Phase der Arzneimittelentwicklung ab. Die high content imaging (HCI)-Technologie offeriert einen Ansatz zur Verbesserung des Durchsatzes verglichen mit der Standardtestbatterie. Zusätzlich hat ein Zell-basiertes Modell den Vorteil Daten relativ schnell bei gleichzeitig geringem Bedarf an Substanzmenge zu generieren. Demzufolge ermöglichen HCI-basierte Testsysteme eine Prüfung in der frühen Phase der pharmazeutischen Arzneimittelentwicklung. Das Ziel dieser Studie ist die Entwicklung eines neuen, spezifischen und sensitiven HCI-basierten Testsytems für Genotoxine und Progenotoxine in vitro unter Verwendung von HepG2-Zellen gewesen. Aufgrund ihrer begrenzten metabolischen Kapazität wurde ein kombiniertes System bestehend aus HepG2-Zellen und einem metabolischen Aktivierungssystem zur Testung progenotoxischer Substanzen etabliert. Basierend auf einer vorherigen Genomexpressionsprofilierung (Boehme et al., 2011) und einer Literaturrecherche wurden die folgenden neun unterschiedlichen Proteine der DNA-Schadensantwort als putative Marker der Substanz-induzierten Genotoxizität ausgewählt: p-p53 (Ser15), p21, p-H2AX (Ser139), p-Chk1 (Ser345) p-ATM (Ser1981), p-ATR (Ser428), p-CDC2 (Thr14/Tyr15), GADD45A und p-Chk2 (Thr68). Die Expression bzw. Aktivierung dieser Proteine wurde 48 h nach Behandlung mit den (pro-) genotoxischen Substanzen (Cyclophosphamid, 7,12-Dimethylbenz[a]anthracen, Aflatoxin B1, 2-Acetylaminofluoren, Methylmethansulfonat, Actinomycin D, Etoposid) und den nicht-genotoxischen Substanzen (D-Mannitol, Phenforminhydrochlorid, Progesteron) unter Verwendung der HCI-Technologie ermittelt. Die beste Klassifizierung wurde bei Verwendung der folgenden fünf der ursprünglichen neun putativen Markerproteine erreicht: p-p53 (Ser15), p21, p-H2AX (Ser139), p-Chk1 (Ser345) und p-ATM (Ser1981). In einem zweiten Teil dieser Arbeit wurden die fünf ausgewählten Proteine mit Substanzen, welche von dem European Centre for the Validation of Alternative Methods (ECVAM) zur Beurteilung der Leistung neuer oder modifizierter in vitro Genotoxizitätstests empfohlen sind, getestet. Dieses neue Testsystem erzielte eine Sensitivität von 80 % und eine Spezifität von 86 %, was in einer Prädiktivität von 84 % resultierte. Der synergetische Effekt dieser fünf Proteine ermöglicht die Identifizierung von genotoxischen Substanzen, welche DNA-Schädigungen durch eine Vielzahl von unterschiedlichen Mechanismen induzieren, mit einem hohen Erfolg. Zusammenfassend konnte ein hochprädiktives Prüfungssystem mit metabolischer Aktivierung für ein breites Spektrum potenziell genotoxischer Substanzen generiert werden, welches sich aufgrund des hohen Durchsatzes, des geringen Zeitaufwandes und der geringen Menge benötigter Substanz zur Substanzpriorisierung und -selektion in der Phase der Leitstrukturoptimierung eignet und darüber hinaus mechanistische Hinweise auf die genotoxische Wirkung der Testsubstanz liefert.

Entity extraction e text classification come strumenti per la sentiment analysis di testi giornalistici

In this thesis we are going to talk about technologies which allow us to approach sentiment analysis on newspapers articles. The final goal of this work is to help social scholars to do content analysis on big corpora of texts in a faster way thanks to the support of automatic text classification.

Classification of organisms previously reported as the SP and Stewart-Letscher groups, with descriptions of Necropsobacter gen. nov. and of Necropsobacter rosorum sp. nov. for organisms of the SP group

To allow classification of bacteria previously reported as the SP group and the Stewart-Letscher group, 35 isolates from rodents (21), rabbits (eight), a dog and humans (five) were phenotypically and genotypically characterized. Comparison of partial rpoB sequences showed that 34 of the isolates were closely related, demonstrating at least 97.4 % similarity. 16S rRNA gene sequence comparison of 20 selected isolates confirmed the monophyly of the SP group and revealed 98.5 %-100 % similarity between isolates. A blast search using the 16S rRNA gene sequences showed that the highest similarity outside the SP group was 95.5 % to an unclassified rat isolate. The single strain, P625, representing the Stewart-Letscher group showed the highest 16S rRNA gene similarity (94.9-95.5 %) to members of the SP group. recN gene sequence analysis of 11 representative strains resulted in similarities of 97-100 % among the SP group strains, which showed 80 % sequence similarity to the Stewart-Letscher group strain. Sequence similarity values based on the recN gene, indicative for whole genome similarity, showed the SP group being clearly separated from established genera, whereas the Stewart-Letscher group strain was associated with the SP group. A new genus, Necropsobacter gen. nov., with only one species, Necropsobacter rosorum sp. nov., is proposed to include all members of the SP group. The new genus can be separated from existing genera of the family Pasteurellaceae by at least three phenotypic characters. The most characteristic properties of the new genus are that haemolysis is not observed on bovine blood agar, positive reactions are observed in the porphyrin test, acid is produced from (+)-L-arabinose, (+)-D-xylose, dulcitol, (+)-D-galactose, (+)-D-mannose, maltose and melibiose, and negative reactions are observed for symbiotic growth, urease, ornithine decarboxylase and indole. Previous publications have documented that both ubiquinones and demethylmenaquinone were produced by the proposed type strain of the new genus, Michel A/76(T), and that the major polyamine of representative strains (type strain not included) of the genus is 1,3-diaminopropane, spermidine is present in moderate amounts and putrescine and spermine are detectable only in minor amounts. The major fatty acids of strain Michel A/76(T) are C(14 : 0), C(16 : 0), C(16:1)omega7c and summed feature C(14 : 0) 3-OH/iso-C(16 : 1) I. This fatty acid profile is typical for members of the family Pasteurellaceae. The G+C content of DNA of strain Michel A/76(T) was estimated to be 52.5 mol% in a previous investigation. The type strain is P709(T) ( = Michel A/76(T) = CCUG 28028(T) = CIP 110147(T) = CCM 7802(T)).

Visual Speech Segmentation: Using Facial Cues to Locate Word Boundaries in Continuous Speech

Speech is typically a multimodal phenomenon, yet few studies have focused on the exclusive contributions of visual cues to language acquisition. To address this gap, we investigated whether visual prosodic information can facilitate speech segmentation. Previous research has demonstrated that language learners can use lexical stress and pitch cues to segment speech and that learners can extract this information from talking faces. Thus, we created an artificial speech stream that contained minimal segmentation cues and paired it with two synchronous facial displays in which visual prosody was either informative or uninformative for identifying word boundaries. Across three familiarisation conditions (audio stream alone, facial streams alone, and paired audiovisual), learning occurred only when the facial displays were informative to word boundaries, suggesting that facial cues can help learners solve the early challenges of language acquisition.

Visual histological grading system for the evaluation of in vitro-generated neocartilage

Here we present the development of a visual evaluation system for routine assessment of in vitro-engineered cartilaginous tissue. Neocartilage was produced by culturing human articular chondrocytes in pellet culture systems or in a scaffold-free bioreactor system. All engineered tissues were embedded in paraffin and were sectioned and stained with Safranin O-fast green. The evaluation of each sample was broken into 3 categories (uniformity and intensity of Safranin O stain, distance between cells/amount of matrix produced, and cell morphology), and each category had 4 components with a score ranging from 0 to 3. Three observers evaluated each sample, and the new system was independently tested against an objective computer-based histomorphometry system. Pellets were also assessed biochemically for glycosaminoglycan (GAG) content. Pellet histology scores correlated significantly with GAG contents and were in agreement with the computer-based histomorphometry system. This system allows a valid and rapid assessment of in vitro-generated cartilaginous tissue that has a relevant association with objective parameters indicative of cartilage quality.